Role: Senior Data Operations Analyst Location: UK, London Job type: Full time, permanent – hybrid Why QS? At QS, our culture fosters a flexible working environment that encourages our employees to own their career whilst personally and professionally thriving. We collaborate, respect and support each other – and as a company, our values underpin these. Our mission is to empower motivated people around the world to fulfil their potential through higher education, and to ensure everyone has the same opportunity to achieve that potential. We celebrate the diversity of our teams and believe through sharing our experiences we can learn from one another and become stronger together, which enables us to achieve our goal. At QS, you’ll be responsible for implementing real change in the international higher education landscape, full of exciting and interesting challenges where you can drive positive impact across the business. In October 2023 we were thrilled to be included in Newsweek’s Top 100 Most Loved Workplaces® in the UK list which is compiled using employee sentiment and satisfaction data. Using insights from more than two million employees in organisations with 50 to 100,000 members of staff, the list recognises workplaces where employees feel most respected and appreciated. As a Senior Data Operations Analyst, this is what you’ll be doing: We're seeking a skilled DataOps Analyst / Data Engineer to join our team. The ideal candidate will play a pivotal role in our university rankings production process, collaborating closely with various teams to ensure timely and accurate delivery. As a hands-on contributor in an Agile environment, you'll be responsible for planning, coordinating, and executing all steps involved. Your duties will include designing, implementing, testing, and maintaining DataOps tools and platforms, building models, and automating workflows. You'll also lead and support data engineers and analysts, streamline processes, and enhance ranking delivery using Snowflake, ELT, Excel, and other relevant systems and tools. Additionally, you'll manage rankings data, ensure data quality, develop reporting routines, provide advanced customer support, and contribute to our quality assurance procedures. Role responsibilities: Rankings Production: Hands-on coordination and planning of all steps related to rankings production in an Agile environment. This involves close collaboration with the broader Data & Analytics team and the Frameworks team among others in the company to ensure timely and accurate delivery of rankings. DataOps & Development: actively engage in the design, implementation, testing, and maintenance of DataOps tools/platforms used for processing data, building ranking models, and automating workflows. Technical Leadership: Lead and support data engineers and data analysts in streamlining processes and improving ranking delivery, leveraging Kleene (ELT platform), Snowflake, and other systems and tools in the QS Data Lake. Where necessary, assume line management, mentorship and coaching responsibility of more junior analysts/engineers. Rankings Data Management: Collaborate in the collection and enrichment of data from various sources, ensuring it meets agreed standards and is loaded into designated storage. Provide feedback to data source owners and set quality requirements for data collection teams. Reporting & Delivery: Develop and maintain routines for generating reports and delivering ranking results in various formats to institutions and internal stakeholders. Provide analytical insights and communicate data work effectively. Customer Support: Provide advanced customer/stakeholder support directly or by upskilling the institutional support team. Quality Assurance: proactively contribute to the design and execution of procedures to ensure the quality of underlying data, intermediary results, and final rankings deliverables. General responsibilities: Develop and Maintain ELT Pipelines: Independently design, build, and manage ELT pipelines to facilitate data integration from a range of sources into Snowflake. Automate the extraction, loading, and transformation of data from various formats including Excel, CSV, XML, Parquet files, and databases (MySQL, PostgreSQL, MongoDB). Enhance Data Quality and Governance: Implement and refine data quality checks and transformation standards to ensure high data integrity within the Data Lake. Collaborate with team members to uphold data governance policies and practices. Support Data Architecture Optimization: Assist in the design of a scalable and efficient data architecture, considering key factors such as performance, security, and cost. Work with senior data engineers to integrate diverse data sources within the ELT process effectively. Automate Data Operations Processes: Identify and execute automation opportunities to streamline data management and ELT workflows. Develop and maintain scripts or tools to enhance data operations efficiency. Troubleshoot and Resolve Data Issues: Take a proactive approach in identifying, diagnosing, and resolving data quality and pipeline issues. Work towards minimizing the impact of data downtime through quick resolution and communication. Implement Automated Quality Assurance Tests: Develop, maintain and integrate automated QA tests to systematically validate data integrity and consistency, ensuring that all data adheres to predefined quality standards before it is deployed. Document Data Processes: Create and update technical documentation for data pipelines, transformations, and data models, ensuring clarity and accessibility for all stakeholders. Collaborate with Cross-functional Teams: Engage with data engineers, analysts, and business stakeholders to gather data requirements and help translate them into technical solutions within the Data Lake environment. Contribute to team discussions on data strategy and business goals, providing insights and suggestions for improvement. Any other duties as required. Key skills and experience: Bachelor's degree in a Science, Technology, Engineering or Mathematical field, or comparable experience in a similar role. Strong experience in data operations or a related data-focused role, with a track record of owning and delivering data projects with some autonomy. Experience in developing manual or automated (desirable) QA models Strong proficiency and/or experience in SQL and scripting languages such as Python. Experience and exposure to a variety of data storage formats (Excel, CSV, XML, Parquet) and familiarity with relational databases (MySQL, PostgreSQL) and NoSQL databases (MongoDB). Knowledge of data quality frameworks, governance practices, and data architecture principles. Strong analytical and problem-solving abilities. Excellent communication skills, with the ability to effectively document and share information. A proactive attitude and the ability to work both independently and collaboratively within a team. So, who are we and what do we do? QS is the world’s leading provider of services, analytics, insights, and intelligence to the global higher education sector - supporting university excellence across the world. Our student recruitment and enrolment solutions enable universities and business schools to connect with talented individuals seeking to further their academic progress and career development. Our portfolio of professional services includes consultancy, student mobility and academic partnerships management, and branding solutions. We publish highly visible and influential rankings of international universities, including the QS World University Rankings® which reaches a global audience of hundreds of millions of people. Founded in 1990, our activities span across 50 countries, working with over 2000 of the world’s leading higher education institutions and over 12,000 employers. Headquartered in London, QS has over 800 employees globally with offices in Australia, Malaysia, India, Romania, Singapore, France, Germany, and the USA. QS keeps growing organically, through acquisition and by recruiting top talent across key regions. We take investing in our people very seriously. As standard you will have: Competitive base salary Access to an annual bonus scheme (for qualifying roles only) 25 days annual leave, plus bank holidays – increasing to 27 days after 5 years’ Enhanced maternity and paternity leave Generous pension through Royal London Comprehensive private medical insurance and wellness scheme through Vitality Access to QSmiles – a discount scheme that actually makes a significant difference Cycle to work scheme A vibrant social environment and multicultural and multinational culture But that’s not all. Outside of these standard benefits we also offer resources to allow professional growth and wellness initiatives to nurture a healthy mindset: Free subscription to the Calm App – the 1 app for sleep, meditation, and relaxation A focus on welfare which is led by our global wellness team, with mental health first aiders globally Access to a variety of diversity and inclusion initiatives and groups Strong recognition and reward programs – including a peer-to-peer recognition platform, quarterly and annual QS Applaud Awards, Connect with your Career annual PD event Support for volunteering and study leave Free subscription to LinkedIn learning – with over 5000 courses and programmes at your fingertips Options to join our outstanding global Mentorship programme Like what you’ve heard? Great, apply now As a candidate, we know the application and interview process can be daunting and so it’s important that you have a great experience with us. Our dedicated Talent Team will work hard to ensure you are fully informed at all stages and you are really excited by this opportunity to do meaningful work in the education space. Equal opportunities QS Quacquarelli Symonds is proud to be a fair and equal organisation where everyone has the same opportunity to achieve their full potential, irrespective of their background or personal attributes. We celebrate our diversity and believe through sharing our experiences we can learn from one another, be stronger together, and enable our business to thrive. Please keep an eye on your spam / junk email folder for correspondence from BambooHR